{"id":"W2624592064","doi":"10.1016/j.marpol.2017.05.030","title":"A rapid assessment of co-benefits and trade-offs among Sustainable Development Goals","year":2017,"lang":"en","type":"article","venue":"Marine Policy","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":422,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of British Columbia","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Sustainability; Sustainable development; Overfishing; Environmental resource management; Context (archaeology); Business; Environmental planning; Environmental economics; Fishing; Political science; Ecology; Economics; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05846623,0.001447401,0.001196891,0.0141249,0.001530478,0.005530998,0.001513064,0.001232481,0.004165315],"category_scores_gemma":[0.08705349,0.0005288661,0.002047441,0.007846874,0.002376588,0.009840146,0.008157633,0.002748074,0.0004969154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005296629,"about_ca_system_score_gemma":0.007754451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006282396,"about_ca_topic_score_gemma":0.01088981,"domain_scores_codex":[0.9677624,0.01627104,0.001729769,0.002067368,0.01110341,0.001065934],"domain_scores_gemma":[0.8977212,0.06752902,0.01224889,0.004104356,0.01723849,0.001158148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003018593,0.0003348386,0.1531412,0.00196252,0.0008657518,0.0007836584,0.007039254,0.04698649,0.003042117,0.267066,0.006090079,0.5123861],"study_design_scores_gemma":[0.00008999374,0.001179228,0.1793242,0.002396578,0.00071754,0.0008450128,0.02498221,0.1508125,0.003764134,0.5759985,0.05936976,0.0005203779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.399664,0.005648134,0.3639376,0.01550882,0.0002705574,0.001916265,0.002356522,0.0005269314,0.2101712],"genre_scores_gemma":[0.8346058,0.001121178,0.1616008,0.0002905051,0.00003878649,0.0005872282,0.0005846873,0.00003421702,0.001136752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05846623,"threshold_uncertainty_score":0.3092027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01337974441988195,"score_gpt":0.2663929561252704,"score_spread":0.2530132117053884,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}